Football Passing Networks is an interactive web application to explore data visualizations on soccer passing networks. Pappalardo, L., Cintia, P., Rossi, A. et al. A public data set of spatio-temporal match events in soccer competitions. Sci Data 6, 236. 2019.

A passing network is just the application of network theory and its analysis tools to understand the performance of a football team in a match. Each player is represented by a vertex. Each vertex is connected with many others by edges, which represent the passes exchanged between players.

Most Goals: Mohamed Salah (Liverpool) - 18. Most Assists: Mohamed Salah (Liverpool) - 13. Most Clean Sheets: Matz Sels (Nottingham Forest) - 9. Big 5: View Big 5 European Leagues together. Become a Stathead & surf this site ad-free. Check out Passing Stats for the 2024-2025 Premier League season.

I'll share the way of creating a passing network for a match between England and Germany of the Euro 2020 from gathering the data to the visualization. There are many events and tracking data providers for soccer. The main ones are Opta, StatsBomb, Prozone, Metrica Sports, Wyscout, and …

Easy-to-use source for football stats including player, team, and league stats.

Football fans can keep a tab on stats related to their favourite team or leagues of interest, and access a wide range of team performance data analytics and league standings, not only on the world's most famous professional leagues, but also on …

This is a site for the objective analysis of Major League Soccer and U.S. Soccer

2022年6月7日 · The Athletic compiled every team’s passing statistics and created an average pass network across all games in the team’s most common starting formation. A team’s passing network says a lot about their style of play, who their most important players are, and how successful the team is.

Set team and match info, and get event and tactics dataframes for the defined match_id

2019年6月25日 · The analysis of passing in elite soccer is common place. Often media shows simple pass counts and pass completion rates but there are much better ways of viewing this type of data. For example, we can create a passing network based on the average position of players when making a pass.